{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CAdam optimizer demo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n"
     ]
    }
   ],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "import numpy as np\n",
    "import os, glob\n",
    "#import seaborn as sns\n",
    "\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "from IPython.display import set_matplotlib_formats, clear_output\n",
    "set_matplotlib_formats('retina')\n",
    "plt.style.use('seaborn-whitegrid')\n",
    "plt.rcParams['figure.figsize'] = (12.0, 7.0)\n",
    "\n",
    "from typing import *\n",
    "import torch\n",
    "from torch import Tensor\n",
    "import sys, os, shutil\n",
    "import pandas as pd\n",
    "\n",
    "ROOT_PROJECT =  os.path.join(os.path.normpath(os.path.join(os.getcwd(), \"../\"))) \n",
    "sys.path[0] = ROOT_PROJECT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from custom_optimizer.cadam import CAdam"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Problem definition"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We consider the following nested-function $J: \\mathbb{R}^2 \\to \\mathbb{R}$ to maximise:\n",
    "\n",
    "$$J(X) = f\\left(\\mathbb{E}_{w\\sim \\mathbb{U}\\{1, 2\\}}\\left[g_w(X)\\right]\\right)$$\n",
    "where\n",
    "$$g_w(X) = \\begin{pmatrix} X_1 \\mathbb{1}_{w=1} & X_2 \\mathbb{1}_{w=2} \\end{pmatrix}^\\top \\in \\mathbb{R}^2, \\qquad f(Y) = \\cos(Y_1)  - |\\sin(Y_2) - 0.2|$$\n",
    "on the domain $[-2, 2]^2$\n",
    "\n",
    "To optimise this compositional objective function $J$ we can use [`CAdam` optimiser ](https://arxiv.org/pdf/2002.03755.pdf).\n",
    "\n",
    "To do so, we simply need to define $f$ and an oracle that can be queried to estimate inner function value and gradient."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_samples = 10\n",
    "\n",
    "def oracle_g(X):\n",
    "    aux = np.random.randint(0, n_samples + 1)\n",
    "    Y = torch.zeros(X.shape)\n",
    "    Y[..., 0] = aux * X[..., 1] * X[..., 0]\n",
    "    Y[..., 1] = (n_samples - aux) * X[..., 1]\n",
    "    return Y / n_samples\n",
    "\n",
    "def f(Y):\n",
    "    return torch.cos(Y[..., 0])   - (torch.sin(Y[..., 1])-.2).abs()\n",
    "\n",
    "# Exact expression for inner expected value is known for this toy example so we will use it to assess \n",
    "# the performance of the optimisation \n",
    "def expected_g(X):\n",
    "    \"\"\" Expected value of g_w(X)\"\"\"\n",
    "    z = torch.zeros(X.shape)\n",
    "    z[..., 0] = X[..., 0] * X[..., 1]\n",
    "    z[..., 1] = X[..., 1]\n",
    "    return X / 2\n",
    "\n",
    "\n",
    "bounds = torch.zeros(2, 2)\n",
    "bounds[0] = -2\n",
    "bounds[1] = 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Optimisation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "seed = 1\n",
    "np.random.seed(seed)\n",
    "torch.manual_seed(seed)\n",
    "\n",
    "# random initialisation\n",
    "X = torch.rand(2).mul(4).add(-2).requires_grad_(True)\n",
    "Y = oracle_g(X).detach().requires_grad_(True)\n",
    "\n",
    "optimizer = CAdam(params=(dict(params=X), dict(params=Y)),lr=.2)\n",
    "\n",
    "# Keep `X` in the domain \n",
    "proj_x = lambda x: x.minimum(bounds[1]).maximum(bounds[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Main loop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "Xs = []\n",
    "for step in range(1000):\n",
    "    n_samples = int((1 + step) ** (4 /5)) \n",
    "    optimizer.zero_grad()\n",
    "    f_Y = - f(Y)\n",
    "    f_Y.backward()\n",
    "    g_X = optimizer.step(oracle_g=oracle_g)\n",
    "    X.data = proj_x(X).data\n",
    "    if step % 5 == 0:\n",
    "        with torch.no_grad():\n",
    "            value_function = f(g_X).item()\n",
    "#         print(f'{step: 5d}: f(E[g(X)]) ≈ {value_function:.2f} {X, Y}')\n",
    "        Xs.append(X.detach().clone().numpy())\n",
    "Xs = np.array(Xs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualize results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 864x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 494,
       "width": 775
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "n = 1000\n",
    "u = v = np.linspace(-2, 2, n)\n",
    "U, V = np.meshgrid(u, v)\n",
    "Z = torch.zeros(*U.shape, 2)\n",
    "Z[..., 0] = torch.tensor(U)\n",
    "Z[..., 1] = torch.tensor(V)\n",
    "z = f(expected_g(Z)).numpy()\n",
    "optim_ind = np.unravel_index(z.argmax(), z.shape)\n",
    "func_optimizer = torch.tensor([U[optim_ind], V[optim_ind]])\n",
    "\n",
    "plt.contourf(U, V, z, cmap=plt.cm.cool)\n",
    "plt.colorbar()\n",
    "plt.title('$f(\\mathbb{E}_w[g_w(X)])$', fontsize=15)\n",
    "plt.xlabel('$X_1$', fontsize=15)\n",
    "plt.ylabel('$X_2$', fontsize=15)\n",
    "plt.scatter(func_optimizer[0], func_optimizer[1], marker='*', s=800, c='g', label='Optimizer')\n",
    "plt.scatter([], [], c='grey', s=20, label='Trajectory')\n",
    "dist_to_optim = np.linalg.norm(func_optimizer.numpy() - Xs[-1])\n",
    "plt.scatter(df.x1, df.x2, s=20, c=df.index, cmap=plt.cm.binary)\n",
    "plt.scatter(Xs[-1, 0], Xs[-1,1], c='k', s=50, marker='D', label=f'Final point (distance to optimizer: {dist_to_optim:.3f})')\n",
    "plt.scatter(Xs[0, 0], Xs[0,1], c='yellow', s=50, marker='D', label=f'Initial point')\n",
    "plt.legend(fontsize=15, bbox_to_anchor=[0.5, -.6, .5,.5], ncol=2)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
